Data processing tools and techniques continue to improve. Information in the form of data is continually being generated or otherwise identified, collected, stored, shared, and analyzed. Databases and other like data repositories are common place, as are related communication networks and computing resources that provide access to such information.
The Internet is ubiquitous; the World Wide Web provided by the Internet continues to grow with new information seemingly being added every second. To provide access to such information, tools and services are often provided, which allow for the copious amounts of information to be searched through in an efficient manner. For example, service providers may allow for users to search the World Wide Web or other like networks using search engines. Similar tools or services may allow for one or more databases or other like data repositories to be searched.
With so much information being available, there is a continuing need for methods and systems that allow for pertinent information to be analyzed in an efficient manner. Search engines, such as, for example, those provided over the web by Yahoo!, Google, and other web sites may be used by individuals to gather information. Typically, a user may input a query term and/or phrase and the search engine may return one or more links to sites and/or documents related to the query. The links returned may be related, or they may be completely unrelated, to what the user was actually looking for. The “relatedness” of results to the query may be in part a function of the actual query entered as well as the robustness of the search system (underlying collection system) used.
Growth in the number of available web pages may make searching for relevant information difficult. To this end, various search engines have been developed over the last decade. One of the components of a search engine may rank electronic documents corresponding to a query specified by a user in order of relevance. Such document ranking may be done based on a multitude of metrics such as degree of query match and freshness of the document. Other metrics may be utilized in advanced rankings of electronic documents to improve the quality of search results. However, such an increase in metrics may adversely affect the query processing time.
Reference is made in the following detailed description to the accompanying drawings, which form a part hereof, wherein like numerals may designate like parts throughout to indicate corresponding or analogous elements. It will be appreciated that for simplicity and/or clarity of illustration, elements illustrated in the figures have not necessarily been drawn to scale. For example, the dimensions of some of the elements may be exaggerated relative to other elements for clarity. Further, it is to be understood that other embodiments may be utilized and structural and/or logical changes may be made without departing from the scope of claimed subject matter. It should also be noted that directions and references, for example, up, down, top, bottom, and so on, may be used to facilitate the discussion of the drawings and are not intended to restrict the application of claimed subject matter. Therefore, the following detailed description is not to be taken in a limiting sense and the scope of claimed subject matter defined by the appended claims and their equivalents.